Visible to the public Precisional Detection Strategy for 6LoWPAN Networks in IoT

TitlePrecisional Detection Strategy for 6LoWPAN Networks in IoT
Publication TypeConference Paper
Year of Publication2022
AuthorsMbarek, Bacem, Ge, Mouzhi, Pitner, Tomás
Conference Name2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Date PublishedOct
Keywords6LoWPAN, composability, Internet of Things, Intrusion detection, IoT, Network, Network security, Protocols, pubcrawl, resilience, Resiliency, security, simulation, Time factors, Wireless sensor networks
Abstract

With the rapid development of the Internet of Things (IoT), a large amount of data is exchanged between various communicating devices. Since the data should be communicated securely between the communicating devices, the network security is one of the dominant research areas for the 6LoWPAN IoT applications. Meanwhile, 6LoWPAN devices are vulnerable to attacks inherited from both the wireless sensor networks and the Internet protocols. Thus intrusion detection systems have become more and more critical and play a noteworthy role in improving the 6LoWPAN IoT networks. However, most intrusion detection systems focus on the attacked areas in the IoT networks instead of precisely on certain IoT nodes. This may lead more resources to further detect the compromised nodes or waste resources when detaching the whole attacked area. In this paper, we therefore proposed a new precisional detection strategy for 6LoWPAN Networks, named as PDS-6LoWPAN. In order to validate the strategy, we evaluate the performance and applicability of our solution with a thorough simulation by taking into account the detection accuracy and the detection response time.

DOI10.1109/SMC53654.2022.9945346
Citation Key9945346